Senior ML Ops Engineer (AI)

TL;DR

Senior ML Ops Engineer (AI): Automating and orchestrating machine learning workflows and developing MLOps solutions for AI-based features (GenAI, Agentic AI, RAG) for hirify.global’s Health platforms. Focus on designing and implementing engineering components for GAR+RAG systems, optimizing infrastructure costs, and ensuring reproducibility and governance of ML models.

Location: Home-based in the US (Connecticut, Georgia, New Jersey, Pennsylvania, Virginia)

Salary: $95,300–$171,954 USD depending on location (e.g., New Jersey: $107,646–$171,954)

Company

hirify.global is a renowned global information analytics company that primarily focuses on providing scientific, technical, and medical (STM) research content, tools, and services.

What you will do

• Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and OpenAI).
• Maintain and version model registries and artifact stores to ensure reproducibility and governance.
• Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment.
• Implement ML Engineering solutions using MLOps platforms such as AWS SageMaker, MLflow, Azure ML.
• Design and implement engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search).
• Build evaluation pipelines for offline IR metrics and LLM quality metrics.

Requirements

• Current experience in ML Engineering, MLOps platforms, and shipping ML or search/GenAI systems to production.
• Hands-on experience with major cloud vendor solutions (AWS, Azure and/or Google).
• Experience with Search/vector/graph technologies (e.g., Elasticsearch, OpenSearch, Solr, Neo4j).
• Experience in evaluating LLM models.
• A strong understanding of the Data Science Life Cycle.
• Work authorization for the USA is required.

Nice to have

• Strong Python, Java, and/or Scala experience.
• Background in health technology and/or medical content workflows.
• Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark.
• Experience with large-scale data processing systems, e.g., Spark.
• Experience with statistical analysis, machine learning theory and natural language processing.

Culture & Benefits

• Work for a mission-driven global organization impacting society.
• Commitment to employee well-being and happiness for a long and successful career.
• Access to country-specific benefits.
• Fair and accessible hiring process with accommodations for disabilities.
• Equal opportunity employer.